Triple
T34683707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Free Imperial City of Biberach |
E890684
|
entity |
| Predicate | hadMixedConfession |
P45699
|
FINISHED |
| Object | yes |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: yes | Statement: [Free Imperial City of Biberach, hadMixedConfession, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMixedConfession Context triple: [Free Imperial City of Biberach, hadMixedConfession, yes]
-
A.
hadMixedConfessionalHistory
chosen
Indicates that an entity has a history involving more than one religious confession or denominational affiliation over time.
-
B.
hadConfession
Indicates that one entity confessed something to another entity or made a formal admission of guilt or wrongdoing.
-
C.
containsConfession
Indicates that one entity includes or expresses an admission of guilt, wrongdoing, or previously concealed truth regarding another entity or situation.
-
D.
usesConfession
Indicates that one entity employs or relies on a confession (typically an admission of guilt or wrongdoing) as part of its actions or reasoning toward another entity or outcome.
-
E.
madePublicConfessionAt
Indicates that an entity openly admitted or confessed something in a public setting at a specific time or place.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f349dabc008190a18999c26682ed47 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7232a16a081909b775efc60b45244 |
completed | May 3, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69f72157af108190880317a62e634bb0 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:05 a.m.